In this document, we refer to the DIKW pyramid, also known variously as the DIKW hierarchy. The DIKW pyramid represents structural and/or functional relationships between data, information, knowledge and wisdom, and is described e.g. Zins, C., “Conceptual Approaches for Defining Data, Information, and Knowledge”, Journal of the American Society for Information and Technology, Feb. 15, 2007; pp 479-493, Wiley InterScience.
In the context of DIKW, data is conceived of as symbols or signs, representing stimuli or signals that are “of no use until . . . in a usable form.” Data can be characterized “as being discrete, objective facts or observations, which are unorganized and unprocessed and therefore have no meaning or value because of lack of context and interpretation.” In short, data can here be defined as “chunks of facts about the state of the world.”
Further, in the context of DIKW, information “is contained in descriptions” and is differentiated from data in that it is “useful.” More precisely, “information is inferred from data” in the process of answering interrogative questions (e.g., “who?”, “what?”, “where?”, “how many?”, “when?”), thereby making the data useful for “decisions and/or action.” In other words, information can be defined as “data that are endowed with meaning and purpose.”
The knowledge component of DIKW is generally agreed to be an elusive concept, which is somewhat difficult to define. The DIKW view is that knowledge is defined with reference to information, for example “as information having been processed, organized or structured in some way, or else as being applied or put into action.” Knowledge can also be referred to as “a fluid mix of framed experience, values, contextual information, expert insight and grounded intuition that provides an environment and framework for evaluating and incorporating new experiences and information.”
Although commonly included as a level in DIKW, there is limited reference to wisdom in discussions of the model. Nevertheless, under the DIKW concept, wisdom can be described as “know-why”, or “why do” (in contrast to “why is”, which is information), Wisdom can also be expanded to include a form of know-what (“what to do, act or carry out”). In general terms, wisdom can be described as “integrated knowledge—information made super-useful”.
In any case, processing the immense amounts of digital data produced by for example information-sensing Internet-of-things devices, such as mobile devices, aerial (remote sensing), software logs, cameras, microphones, radio-frequency identification readers and wireless sensor networks into information and/or knowledge is a highly complex task. Maintaining data integrity is also important to ensure the quality of the resulting information and/or knowledge.